Triple

T17201141
Position Surface form Disambiguated ID Type / Status
Subject Wat Tyler E417475 entity
Predicate hasGivenName P17 FINISHED
Object Walter E32053 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Walter | Statement: [Wat Tyler, hasGivenName, Walter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Walter
Context triple: [Wat Tyler, hasGivenName, Walter]
  • A. Walter chosen
    Walter is a masculine given name of Germanic origin that has been widely used in English-speaking countries.
  • B. Walter
    Walter is the central figure known as "The Woodsman," a character defined by his rugged life in the forest and the moral or psychological struggles that accompany his isolation.
  • C. Walter
    Walter is a grumpy, sharp-tongued old-man puppet character featured in Jeff Dunham’s stand-up comedy acts.
  • D. Walter Haut
    Walter Haut was a former U.S. Army Air Force public information officer best known for issuing the 1947 Roswell UFO press release and later co-founding the International UFO Museum and Research Center.
  • E. Wilbert
    Wilbert is the given first name of American character actor Bill Cobbs, known for his numerous supporting roles in film and television.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d886d6ba8c819093215917b3d01689 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42daf2e5c81909c97d2e7a3ed7b88 completed April 19, 2026, 1:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a015fda06788190882aef1a57356e41 completed May 11, 2026, 4:49 a.m.
Created at: April 10, 2026, 5:38 a.m.